Evolving Scale-free Network Model with Tunable Clustering
نویسندگان
چکیده
The Barabási-Albert (BA) model is extended to include the concept of local world and the microscopic event of adding edges. With probability p, we add a new node with m edges which preferentially link to the nodes presented in the network; with probability 1− p, we add m edges among the present nodes. A node is preferentially selected by its degree to add an edge randomly among its neighbors. Using continuum theory and rate equation method we get the analytical expressions of the power-law degree distribution with exponent γ = 3 and the clustering coefficient c(k) ∼ k + c. The analytical expressions are in good agreement with the numerical calculations.
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